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Partially Identified Poverty Status: A New Approach to Measuring Poverty and the Progress of the Poor

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Author Info

  • Gordon Anderson
  • Maria Grazia Pittau
  • Roberto Zelli

Abstract

Poverty measurement and the analysis of the progress (or otherwise) of the poor is beset with difficulties and controversies surrounding the definition of a poverty line or frontier. Here, using ideas from the partial identification literature and mixture models, a new approach to poverty measurement is proposed which avoids specifying a frontier, the price is that an agent's poverty status is only partially identified. Invoking variants of Gibrat's law to give structure to the distribution of outcomes for homogeneous subgroups of a population within the context of a finite mixture model of societal outcomes facilitates calculation of the probability of an agent's poverty status. From this it is straightforward to calculate all the usual poverty measures as well as other characteristics of the poor and non poor subgroups in a society. These ideas are exemplified in a study of 47 countries in Africa over the recent quarter century which reveals among other things a growing poverty rate and a growing disparity between poor and non poor groups not identified by conventional methods.

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Bibliographic Info

Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-421.

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Length: 28 pages
Date of creation: 20 Jan 2011
Date of revision:
Handle: RePEc:tor:tecipa:tecipa-421

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Related research

Keywords: Poverty Frontiers; Mixture Models; Gibrat\'s law; Partial Identification;

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  1. Duclos, Jean-Yves & Sahn, David & Younger, Stephen D., 2001. "Robust Multidimensional Poverty Comparisons," Cahiers de recherche 0115, Université Laval - Département d'économique.
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  1. Partially Identified Poverty Status: A New Approach to Measuring Poverty and the Progress of the Poor
    by maximorossi in NEP-LTV blog on 2011-02-01 15:31:06
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Cited by:
  1. Anderson, Gordon, 2011. "Polarization measurement and inference in many dimensions when subgroups can not be identified," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 5(11), pages 1-19.

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